Alzheimer?s disease (AD) has a strong genetic basis but is not well understood. The two main categories of AD are early-onset AD (EOAD; onset ? 65 years) and late-onset AD (onset >65 years). The former is rare but has a much higher genetic basis than the latter. Notably, studies of families with EOAD have paved the way to a broader understanding of how AD develops. Indeed, studying EOAD led to the discovery of three genes - amyloid precursor protein [APP], presenilin 1 [PSEN1] and presenilin 2 [PSEN2]). Identification of these three AD genes was pivotal in establishing the role of beta-amyloid in the development of AD. Therefore, studying EOAD promises to provide novel insights for both EOAD in particular and AD in general. Here, we propose to study individuals with EOAD to identify novel genetic causes of AD. We note that >90% of individuals with EOAD do not carry one of the known AD-causing mutations, yet still develop EOAD at exceptionally young ages. Thus, these individuals are likely to harbor new genetic variants of high effect that can provide crucial insights into AD pathogenesis. Here, we present exciting and novel data showing that genes previously known to regulate plasma cholesterol contribute to EOAD. Our novel data lay a foundation for further hypothesis-driven genetic studies of contribution of lipid metabolism to EOAD pathogenesis. Here, we propose three complementary aims to gain new insight into AD pathogenesis. In the first aim, we propose a 2-stage genetic study to identify new genes for EOAD. In the first stage, the discovery dataset (n=3,142) will undergo next-generation sequencing for loci known to control plasma cholesterol and test whether these loci are associated with EOAD. Significant findings will be confirmed in our replication dataset (n=400). Based on our preliminary results we anticipate, that EOAD will associate with genes known to influence plasma cholesterol. In aim 2, we propose to determine whether genes known to regulate cholesterol contribute to EOAD through their influence on plasma cholesterol or through an independent mechanism. This aim will utilize Mendelian randomization and enables us to gain mechanistic insights into the genes identified in our preliminary data and aim 1. Finally, we propose to test whether the genes and variants that influence LDLc also contribute to AD pathology using the ROS/MAP cohorts, which have ~1700 individuals who have undergone autopsy and whole-genome sequencing. Similar to Aims 1-2, we will use ask whether significant associations act through plasma cholesterol using Mendelian randomization approach. Findings from the proposed work are likely to have high public health impact in i) elucidating novel genetic causes for, ii) identifying biomarkers for early detection of AD, and iii) suggesting novel prevention trials that target lowering plasma cholesterol levels in at risk individuals.